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--- |
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language: |
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- ko |
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license: apache-2.0 |
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base_model: openai/whisper-base |
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tags: |
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- hf-asr-leaderboard |
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- generated_from_trainer |
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datasets: |
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- mozilla-foundation/common_voice_13_0 |
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model-index: |
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- name: oceanstar-bridze |
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results: [] |
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metrics: |
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- cer |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# oceanstar-bridze |
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This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the bridzeDataset dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1880 |
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- Cer: 7.3894 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 1e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 500 |
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- training_steps: 4000 |
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### Training results |
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| Training Loss | Epoch | Step | Cer | Validation Loss | |
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|:-------------:|:-----:|:----:|:-------:|:---------------:| |
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| 0.3652 | 0.06 | 500 | 11.3504 | 0.3574 | |
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| 0.2788 | 0.13 | 1000 | 9.1325 | 0.2645 | |
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| 0.2213 | 0.1 | 1500 | 9.3132 | 0.2388 | |
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| 0.2257 | 0.13 | 2000 | 8.6295 | 0.2194 | |
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| 0.1941 | 0.16 | 2500 | 7.5109 | 0.2068 | |
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| 0.1395 | 0.19 | 3000 | 7.3247 | 0.1969 | |
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| 0.1787 | 0.23 | 3500 | 7.5517 | 0.1905 | |
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| 0.1639 | 0.26 | 4000 | 7.3894 | 0.1880 | |
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### Framework versions |
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- Transformers 4.32.0.dev0 |
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- Pytorch 1.10.1 |
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- Datasets 2.14.2 |
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- Tokenizers 0.13.3 |
